Chatbot/ML/AI Development

A chatbot is a software program for simulating intelligent conversations with human using rules or artificial intelligence. Users interact with the chatbot via conversational interface through written or spoken text. E.g. Slackbot, Facebook bots, etc.

In recent years, Chatbots have demonstrated the power and convenience of conversational interfaces. As of now, language is emerging as the interface in connecting brands with their users. Chatbots these days are being built to handle user requests, provide relevant information and be the friend one would look for to seek information.

So, if you believe the above to be important, then yes, Chatbots are very good.

Building a chatbot can be challenging, but with a keen eye for details, you can build a chatbot that offers great value. The plan to build a chatbot must also ascertain the purpose for building the bot, knowing what problem the bot is going to solve.
Chatbots can be built in two ways –

• Rule-based approach resulting in hard coding.
• Machine learning that necessitates streaming data for the system to learn on its own.

There are two ways to chatbots - the basic chatbots and then there are chatbots with AI (Artificial Intelligence) brains. If you have customers wanting to converse with chatbots that understand natural language, you will need bot that is rich in AI so it would learn and adapt to your user’s needs.

There are many AI available for each person’s needs out there. Some AI we at Hureka would recommend are:

• Microsoft bot frameworks.
• Wit.ai.
• Api.ai.
• IBM’s Watson.
• Motion.ai
• Chatfuel.

Chatbots can have a number of uses, from greeting and welcoming users on your website to, getting their contact information to talking to them about your brand and business, chatbots are the perfect digital representatives of your business.
For example, with an online food discovery project here at Hureka called Palatable (www.palatable.app), we take the case of a user asking the chatbot to suggest the best place for eating. Here, the chatbot must understand what the user wants, provide a proper response – In this case, provide the name of the best restaurants based on the user’s profile, though the user has mentioned it as ‘place’. This is achieved through goof Natural Language Processing (NLP).

Machine Learning is the science of getting computers to learn and act like humans do, and improve their learning over time in autonomous fashion, by feeding them data and information in the form of observations and real-world interactions.

Machine learning has been used in multiple fields and industries. For example, medical diagnosis, image processing, prediction, classification, learning association, regression etc.

We at Hureka Technologies offer Machine Learning to assist our clients with the following:

• Natural Language Processing and Speech recognition.
• Learning Associations.

1.     Natural language processing is a subfield of linguistics, computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human languages, in particular how to program computers to process and analyze large amounts of natural language data. Examples of NLP tools are:

a.       Microsoft LUIS.

b.       Wit.ai

c.       Api.ai

Learning associations is the process of developing insights into the various associations between the products.

For example, associating different products with each other.

A real world application of machine learning is studying the associations between people and their purchase decisions. This is then used to offer him suggestions, because there is a relation between the two products. 

A chatbot is a software program for simulating intelligent conversations with human using rules or artificial intelligence. Users interact with the chatbot via conversational interface through written or spoken text. E.g. Slackbot, Facebook bots, etc.

In recent years, Chatbots have demonstrated the power and convenience of conversational interfaces. As of now, language is emerging as the interface in connecting brands with their users. Chatbots these days are being built to handle user requests, provide relevant information and be the friend one would look for to seek information.
So, if you believe the above to be important, then yes, Chatbots are very good.

Building a chatbot can be challenging, but with a keen eye for details, you can build a chatbot that offers great value. The plan to build a chatbot must also ascertain the purpose for building the bot, knowing what problem the bot is going to solve.
Chatbots can be built in two ways –

1. Rule-based approach resulting in hard coding.
2. Machine learning that necessitates streaming data for the system to learn on its own.

There are two ways to chatbots - the basic chatbots and then there are chatbots with AI (Artificial Intelligence) brains. If you have customers wanting to converse with chatbots that understand natural language, you will need bot that is rich in AI so it would learn and adapt to your user’s needs. The latter bot is called a Natural Language processing or NLP bot.

A flow-based chatbot is one that works by using a pre-defined (and reined in) conversational flow. In other words, they have their conversations already mapped out like a flowchart. When a customer triggers a conversation, the chatbot guides them through the conversation flow chart, step by step, almost like an If-else flow.

A flow-based chatbot’s conversations work toward pre-defined goals, which the bot can tell the user at the start of the chat. This means that from the onset, it’s clear to the user what they can achieve by interacting with the bot.
Plus, the bot guides the user through the conversation, supplying viable answers and asking closed questions.

So, we recommend Flow-based Chatbots in any scenario where you only want to direct your users to fixed goals and outcomes.

Flow-based chatbots can only address and answer the questions they have been programmed to answer. This can make them appear restrictive to the user and often, if the user does not find their query, it can lead to disappointment.